July 24, 2006
Prediction Markets By:
The Internet Gambling Act (HR4411) that passed the House earlier this month is a curious compromise. There’s been a lot of discussion elsewhere about the fact that this bill won’t stop gambling on the Internet, and doesn’t even seem intended to try; I’ll leave that issue alone. The only point I wanted to make is that the bill only covers sports betting (and pure lotteries).
The definitions say
(1)The term `bet or wager'--
(A) means the staking [...] of value upon the outcome of a contest of others, a sporting
event, or a game subject to chance [...];
(B) includes the purchase of a chance [...] to win a lottery (which [...] is predominantly
subject to chance);
(C) includes any scheme described in [Unlawful sports gambling law];
(D) includes any [..] information pertaining to the [...] movement of funds [for] the
business of betting or wagering; and
(E) does not include [commodities, securities, derivatives, insurance, and fantasy sports]
Of course, the lack of coverage of prediction markets in this bill doesn’t make them legal, it just leaves them out of the effects of this bill. Most of the effect of the bill is to make it harder to move funds into and out of gambling accounts, rather than to prohibit anything in particular. It’s not clear whether credit card handlers or banks would notice the distinction, but this may leave an opportunity for someone to run a market long enough to challenge the law.
I think it’s odd that they drew the line so narrowly. But there’s time for the Senate to change that if they pass something, and if there are any differences between the House and Senate versions, anything can happen in reconciliation.
July 19, 2006
Prediction Markets By:
Previous articles have described a few simple formats of prediction market: simple double auctions, markets with open-ended prices, the symmetry of complementary purchases, and how to integrate an order book with an automated market maker. In this article, I describe the mechanics of multi-outcome markets, both as most markets currently implement them, and as I expect to implement them in the Zocalo Prediction Market. I’ve presented this idea before, so you can get another look at the idea by reviewing my slides. ( PowerPoint 3MB).
The basic idea is that instead of two exclusive outcomes, you want the market to give a prediction about an event that might turn out in one of three or more ways. Canonical examples include an election with multiple candidates running, or a tournament among some number of teams. The straightforward approach is to create a pair of assets for each candidate, representing respectively, that competitor’s chances of winning and losing. This way you end up with N separate markets, and each one has a price for buying and selling the particular candidate that gives their chance of winning. The same general idea can be used to turn a continuous variable (how many widgets will we sell? What will the temperature in San Jose be on August 27th?) into a series of discrete choices. I’ll talk about those kinds of markets later.
July 15, 2006
Prediction Markets By:
MIT’s Center for Coordination Science has recast itself as the Center for Collective Intelligence. Tom Malone (who spoke at the New York Prediction Market Summit), and Tomaso Poggio (who co-authored Securities Trading of Concepts) are two of the principals. The new center’s framing question is How can people and computers be connected so that—collectively—they act more intelligently than any individuals, groups, or computers have ever done?. Prediction Markets are explicitly on the agenda. Their proposed (and ongoing) research includes:
- How can large groups of people produce high quality written documents?
- How can groups of people make accurate predictions of future events? For instance, in prediction markets, people buy and sell predictions about uncertain future events, and the prices that emerge in these markets are often better predictors than opinion polls or individual experts. When and how do these prediction markets work best? How can they be combined with simulations, neural nets, and other techniques? (emphasis added)
- How can we harness the intelligence of thousands of people around the world to help solve the problems of global climate change?
- How can we create an on-line, searchable library of books from many languages and historical eras?
- How can we help create commercially sustainable products and services for low-income communities around the world?
This focus is strongly related to Marty Tenebaum’s proposals in his AAAI invited talk and PARC Forum on collaboration between people and intelligent agents on the modern web. (In addition to being at the heart of what’s most valuable about Web 2.0.)
Other distinguished faculty include Deborah Anacona, Rodney Brooks, and Alex Pentland. Marty’s son Josh Tenenbaum is also on the faculty.
The center is new enough that their websites don’t appear to be in their final locations. cci.mit.edu still has the old center’s pages, while the new center is at learning.mit.edu. If the links move around, that’s probably why.
Congratulations on the creation of the new center, and good luck!
ADDENDUM: Apparently I jumped the gun with this annoucement. The center is now up at cci.mit.edu, and learning.mit.edu has been discontinued. I changed the link under the first mention of the center’s new name.
July 15, 2006
Prediction Markets By:
In response to a couple of requests for installation help, I spent most of the week figuring out how to install under Windows, and how to generate appropriate zip files. I have uploaded a new release of the Zocalo Prediction Market Software to SourceForge. There are now 5 different files you can choose from in order to run Experiments or Prediction Markets, on Windows (zip) or unix-based platforms (tar.gz), or to get a copy of the entire source tree.
I’m embarassed to admit that I broke the Experiments in the last release, but they should be fixed.
On another note, while I was poking around SourceForge the other day, I noticed that they keep statistics on downloads and visits. The statistics on downloads didn’t have any interesting consistency, and I think the “project web traffic” means my use to check-in changes and maintain the code, but this graph of traffic sure looks interesting. A steadily growing number of visits is good. Thanks for your interest. I plan to keep improving Zocalo; I hope to justify your continued interest.
June 30, 2006
Prediction Markets By:
I released a major new version of Zocalo on SourceForge yesterday. This release is the one I’ve been targeting as good enough for people to test out with interested groups. The user accounts now have password security, and only administrators can create new accounts and set up claims. (Later, I’ll make it possible to configure Zocalo so anyone can create an account and the administrator will be able determine who can create claims. Public access to account creation is waiting until I hook up email for verification. At that point, it will also be possible to send trade results via email.) Claim owners now also have the ability to pay out claims, there’s a new screen for reviewing transaction history, and users get feedback when a trade takes place.
If you have been waiting to use Zocalo to run prediction markets until a few more features are added, this is the first version (since the releases for economics experiments) that has enough functionality to be worth playing with and showing to your friends and colleagues. If you want to make suggestions about what features should be added first, I’d love to hear them. I know of many things that need to be added, but I only have my own guesses at this point about which missing features are show stoppers and what minor features would suffice for some users to deploy significant markets.
In the absence of feedback pointing to particular features that are useful sooner, I’m expecting my next step to be integrating email, so that account creation can be opened up, and the system can send transaction details to traders. I will also do some cleanup and simplification of the order entry form, since I’ve alrady had a request for that.
June 23, 2006
Prediction Markets By:
Eliezor Yudkowsky has written a good review on individual biases for a volume assessing the possibility of global catastrophic risks from AI, Nanotech, Biotech, etc. Yudkowsky’s particular concern is AI, and the likelihood that an AI will take over the world soon after its ascendance if it’s not carefully designed to care about humanity’s wishes. In the process of arguing on this subject, he has spent quite a bit of time becoming an expert on various aspects of epistemology: Bayesian reasoning, cognitive biases, in general how to think, act, and argue rationally. His writings in this area are particularly clear and usually directed to an audience that might not have thought carefully about reasoning.
May 31, 2006
Prediction Markets By:
CommerceNet has been very generous in funding my work on Zocalo for more than a year. From the beginning, it was proposed as an appointment that would last for a year or two, as part of CommerceNet’s program to bring a variety of people and projects into the labs, both to expose the particular projects to CommerceNet and its partners and to attract other entrepreneurs to visit and raise their new ideas and ventures to CommerceNet’s view. While I’ve been here, I think both sides have benefited: I’ve been able to get more exposure for Zocalo than I would have otherwise, and in getting visibility for Prediction Markets, I’ve also raised CommerceNet’s profile in some interesting arenas.
The next version of Zocalo that I release (sometime in June, I expect) will add the main features that were missing for usable long-term prediction markets. (Secure accounts, transaction history, and access controls for claim creation are checked in to sourceforge‘s subversion repository, paying off claims is coming soon.) I expect to run a couple of private trials (more beta sites would be welcome) and hope to install the software on a public website so people will be able to try it out. I’m also happy that there’s another developer interested in adding some features who is talking issues over with me via email and on sourceforge.
I will continue to work at CommerceNet over the next few months, while I transition back to working on Zocalo on my own. (I was working on the code on my own nickel before CommerceNet offered to hire me and allow the code to remain open source.) I expect to work on Zocalo full-time for the rest of the year, and then spend up to half-time consulting to support continued development. The more consulting I can find that’s related to Zocalo, the less time I’ll have to spend on other work.
It’s been great fun interacting with all the people and companies that have been through here. We had some great interns last summer, and are expecting more this summer. I can’t talk about all the companies that have incubated here, but the folks that Renkoo and NewRoo were certainly cool to work with.
Zocalo’s future? I’m going to continue betting on it for a while.
May 5, 2006
Prediction Markets By:
I’m joining the roster at the Chicago Prediction Market summit.
I’ll try to explain how Zocalo can improve the prospects for adoption of Prediction
Markets in business by making the technology more accessible, and by doing a better
job of publicizing results so more companies may be convinced that this is valuable
technology. I’ll try to argue that the academic results are in and pretty uniformly
positive; the thing that is lacking that would enable or encourage more widespread
adoption is evidence that these markets produce valuable input into organizations’
deliberative processes. The existing companies selling PMs into business haven’t
been able to talk enough about how these markets have helped their customers.
looking forward to hearing what
Cass Sunstein has to say. His article in the Hahn & Tetlock
book is quite interesting. He points out that groups that make decisions as a result
of meetings and discussions make common mistakes in their reasoning, and that markets
seem to have opposite tendencies. In the article, he seems to suggest that markets
should be used instead, but the point about countervailing tendencies suggests that
finding ways to use them together might be a better approach.
background is in competitive intelligence; he’s going to talk about how markets can
be used in exploring the competitive landscape. It will be good to see Robin Hanson,
Justin Wolfers, and Michael Gorham again (all were at the DIMACS event in early
2005), as well as perenials John Delaney (from Tradesports), David Perry (Consensus
Point), and Emile Servan-Schreiber (NewsFutures).
May 5, 2006
Innovation, The Now Economy By:
It’s a Friday afternoon, and I’d like to clean up my desktop with a list o’ links I’ve found interesting over the past few weeks:
The Personal Bee aggregator for VC & Startup news. Feels a bit like some of the concepts behind Newroo/Fox. Here are several stories I got to from there:
- the MIT/Lemelson Prize for inventors goes to an LCD pioneer from Menlo Park.
- Sequoia, via Kedrosky:
E&Y: Why is it crazy that LPs are willing to invest so much in venture capital?
Leone: The returns have been miserable. If you take away a couple of exits, such as Google and MySpace, there haven’t been meaningful returns generated. There are [venture] firms that have never generated a positive return or have not even returned capital in 10 years that are raising money successfully. And that surprises the heck out of me. People talk about the top quartile — its not about the top quartile, it’s barely about the top decile, or even a smaller subset than that.
- Khosla Ventures actually does still invest in computer-related stuff, not just the cool new life- and green- sciences, from this BusinessWeek blogpost by Justin Hibbard:
one of his inaugural portfolio companies was SkyBlue Technologies, Inc. The Redwood City (Calif.) startup was founded a year ago by Stanford U. computer science professor Monica S. Lam and her fellow researchers, who are developing open-source virtualization software that lets systems administrators remotely manage PCs. Traditionally, companies have used programs like CA’s Unicenter or HP OpenView for this task. Virtualization sacrifices some performance to keep the management program running independently from the PC operating system, which can become unstable. It’s a clever use of an under-exploited technology that has had a recent resurgence on server computers and has produced at least one recent hit startup, VMWare. SkyBlue calls its class of software ready-to-run (R2R) and has launched a portal site, itCasting, to promote collaboration on R2R software. William J. Raduchel, CEO of Ruckus Network and former CTO at AOL Time Warner, is on SkyBlue’s board. The company raised $1 million last August and $2.26 million from Khosla and others in March.
[In other recent manageability news, Intel announced vPro, a desktop featureset hopefully-analgous to Centrino, raising the possibility of yet-more feature wars such as XML processing smarts on the server side. ]
The New York Times recently had a piece on academics investigating the IBM-sponsored “services science” field
ComputerWorld’s Gary Anthes, a dedicated reporter on the research-and-innovation beat, wrote a piece on the looming anniversaries of the oldest CS departments.:
- John Canny, chairman of the electrical engineering and computer science department, University of California, Berkeley: “Computers aren’t very valuable yet, because the applications they perform are still elementary and routine. It’s actually remarkable how much we spend on IT, considering how little it does. The most widespread applications are still e-mail and Microsoft Office. That should tell us something.
What we really need to be thinking about is what people are doing with computers and how we could help them to do those things much better. Since most people are doing knowledge tasks, that means machines understanding their owners’ work processes much more deeply, finding semantically appropriate resources with or without being asked, critiquing choices and suggesting better ones, and tracking synergies with other groups within a large organization. Computers will leverage the human resources in the company more at a knowledge level. They will directly tie what they do to the creative processes of employees. The economic impact of that would be much bigger than anything we have seen so far. ”
- Jaime Carbonell, director of the Language Technologies Institute, Carnegie Mellon University: “Artificial intelligence. Although those words may be somewhat out of fashion these days, much of the deep excitement and universally useful apps descend therefrom. For example: speech understanding and synthesis in handheld devices, in cars, in laptops; machine translation of text and spoken language; new search engines that find what you want, not just Web pages that contain query words; self-healing software, including adaptive networks that reconfigure for reliability; robotics for mine safety, planetary exploration; prosthetics for medical/nursing care and manufacturing; game theory for electronic commerce, auctions and their design to ensure fairness and market liquidity and maximize aggregate social wealth.”
- Bernard Chazelle, professor of computer science, Princeton University: I roll my eyes when I hear students say, “CS is boring, so I’ll go into finance.” Do they know how dull it is to spend all-nighters running the numbers for a merger-and-acquisition deal? No.
- Canny: We’re losing in quality — principally to bioengineering, which is now the best students’ top choice — and diversity. It’s a problem of social relevance. Minorities and women moved fastest into areas such as law and medicine that have obvious and compelling social impact. We’ve never cared much about social impact in CS.
- Chazelle: Much of the curriculum is antiquated. Why are we still demanding fluency in assembly language today for our CS majors? Some curricula seem built almost entirely around the mastery of Java. This is criminal.
The curriculum is changing to fulfill the true promise of CS, which is to provide a conceptual framework for other fields. Students need to understand there’s more, vastly more, to CS than writing the next version of Windows. For example, at Princeton, we have people who major in CS because they want to do life sciences or policy work related to security, or even high-tech music. In all three cases, we offer tracks that allow them to acquire the technical background to make them intellectually equipped to pursue these cross-disciplinary activities at the highest level.
- Carbonell: CS needs a great communicator who lives the excitement, is deeply respected by his or her peers, and can reach out and communicate clearly with any educated person via his books. We have no such person in CS. Perhaps Raj Reddy [a Carnegie Mellon computer science professor] has the right kind of talents.
Finally, please don’t miss Bill Burnham’s excellent survey of opportunites to push ‘persistent search’ forward.